Abstract

Better risk prediction and new molecular targets are key priorities in type 2 diabetes (T2D) research. Little is known about the role of the urine metabolome in predicting the risk of T2D. We aimed to use non-targeted urine metabolomics to discover biomarkers and improve risk prediction for T2D. Urine samples from two community cohorts of 1,424 adults were analyzed by ultra-performance liquid chromatography/mass spectrometry (UPLC-MS). In a discovery/replication design, three out of 62 annotated metabolites were associated with prevalent T2D, notably lower urine levels of 3-hydroxyundecanoyl-carnitine. In participants without diabetes at baseline, LASSO regression in the training set selected six metabolites that improved prediction of T2D beyond established risk factors risk over up to 12 years' follow-up in the test sample, from C-statistic 0.866 to 0.892. Our results in one of the largest non-targeted urinary metabolomics study to date demonstrate the role of the urine metabolome in identifying at-risk persons for T2D and suggest urine 3-hydroxyundecanoyl-carnitine as a biomarker candidate.

Highlights

  • Better risk prediction and new molecular targets are key priorities in type 2 diabetes (T2D) research

  • This need is underscored by a 2017 survey by the charity Diabetes UK, where a top research priority for persons affected by T2D was to "identify people at high risk of type 2 diabetes and help to prevent the condition from developing"[5]

  • Non-targeted methods such as ultra-performance liquid chromatography coupled to quadrupoletime-of-flight mass spectrometry (UPLC-QTOFMS) capture all metabolite signals detectable by the method at hand without a priori selection

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Summary

Introduction

Better risk prediction and new molecular targets are key priorities in type 2 diabetes (T2D) research. We aimed to use non-targeted urine metabolomics to discover biomarkers and improve risk prediction for T2D. A continuing challenge is the identification of persons at high risk of T2D, in the absence of established risk factors such as obesity and poor ­diet[3,4] This need is underscored by a 2017 survey by the charity Diabetes UK, where a top research priority for persons affected by T2D was to "identify people at high risk of type 2 diabetes and help to prevent the condition from developing"[5]. We use non-targeted UPLC-MS urinary metabolomics in two community-based cohorts of > 1,400 Swedish adults to discover metabolites associated with prevalent T2D and to assess whether urinary metabolomics improves risk prediction of incident T2D beyond an established clinical risk score

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